The COVID-19 Situation Report is a data intensive report that tries to portray an accurate data oriented picture of the 2019- 2020 COVID-19 pandemic. If you would like to add additional metrics to this report, please send a mail to the author at .

Date of Report

Numbers as on EOD 

## [1] "2020-06-01"

COVID-19 Overall Stats (Worldwide)

Overall Confirmed Cases Count Worldwide 

## [1] "6266192 (up from 6166946 yesterday: 1.61 % increase)"

Overall Deaths Worldwide

Please note that the deaths is at the minimum an underestimate as there could be fatalities resulting from the current active cases.

## [1] "375559 (up from 372035 yesterday: 0.95 % increase)"

Overall Fatality Rate Worldwide in %

Please note that the fatality rate is at the minimum an underestimate as there could be fatalities resulting from the current active cases.

## [1] 5.99



In- Depth Country Wise Stats (With Atleast 1000 COVID-19 Confirmations)

Overall Confirmed Cases and Deaths- Country Wise (With Fatality Rates)

Country_Region TotalConfirmed NewConfirmations CasesPercentIncrease TotalDeaths NewDeaths DeathsPercentIncrease FatalityRate
US 1811360 21188 1.18 105165 784 0.75 5.81
Brazil 526447 11598 2.25 29937 623 2.13 5.69
Russia 414328 8485 2.09 4849 156 3.32 1.17
United Kingdom 277736 1580 0.57 39127 556 1.44 14.09
Spain 239638 159 0.07 27127 0 0.00 11.32
Italy 233197 200 0.09 33475 60 0.18 14.35
India 198370 7761 4.07 5608 200 3.70 2.83
France 189348 339 0.18 28836 31 0.11 15.23
Germany 183594 184 0.10 8555 15 0.18 4.66
Peru 170039 5563 3.38 4634 128 2.84 2.73
Turkey 164769 827 0.50 4563 23 0.51 2.77
Iran 154445 2979 1.97 7878 81 1.04 5.10
Chile 105158 5470 5.49 1113 59 5.60 1.06
Mexico 93435 2771 3.06 10167 237 2.39 10.88
Canada 93288 809 0.87 7404 30 0.41 7.94
Saudi Arabia 87142 1881 2.21 525 22 4.37 0.60
China 84154 8 0.01 4638 0 0.00 5.51
Pakistan 72460 2964 4.26 1543 60 4.05 2.13
Belgium 58517 136 0.23 9486 19 0.20 16.21
Qatar 58433 1523 2.68 40 2 5.26 0.07
Bangladesh 49534 2381 5.05 672 22 3.38 1.36
Netherlands 46749 104 0.22 5981 6 0.10 12.79
Belarus 43403 847 1.99 240 5 2.13 0.55
Ecuador 39098 0 0.00 3358 0 0.00 8.59
Sweden 37814 272 0.72 4403 8 0.18 11.64
Singapore 35292 408 1.17 24 1 4.35 0.07
United Arab Emirates 35192 635 1.84 266 2 0.76 0.76
South Africa 34357 1674 5.12 705 22 3.22 2.05
Portugal 32700 200 0.62 1424 14 0.99 4.35
Switzerland 30871 9 0.03 1920 0 0.00 6.22
Colombia 29384 2165 7.95 963 47 5.13 3.28
Kuwait 27762 719 2.66 220 8 3.77 0.79
Indonesia 26940 467 1.76 1641 28 1.74 6.09
Egypt 26384 1399 5.60 1005 46 4.80 3.81
Ireland 25062 72 0.29 1650 -2 -0.12 6.58
Ukraine 24562 890 3.76 724 16 2.26 2.95
Poland 24165 379 1.59 1074 10 0.94 4.44
Romania 19398 141 0.73 1276 10 0.79 6.58
Philippines 18638 552 3.05 960 3 0.31 5.15
Dominican Republic 17572 287 1.66 502 0 0.00 2.86
Argentina 17415 564 3.35 556 17 3.15 3.19
Israel 17169 98 0.57 285 0 0.00 1.66
Japan 16787 36 0.21 899 1 0.11 5.36
Austria 16733 2 0.01 668 0 0.00 3.99
Afghanistan 15750 545 3.58 265 8 3.11 1.68
Panama 13837 374 2.78 344 8 2.38 2.49
Oman 12223 786 6.87 50 1 2.04 0.41
Denmark 11899 30 0.25 576 2 0.35 4.84
Bahrain 11871 473 4.15 19 0 0.00 0.16
Korea, South 11541 38 0.33 272 1 0.37 2.36
Serbia 11430 18 0.16 244 1 0.41 2.13
Kazakhstan 11308 450 4.14 41 1 2.50 0.36
Nigeria 10578 416 4.09 299 12 4.18 2.83
Bolivia 10531 549 5.50 343 30 9.58 3.26
Algeria 9513 119 1.27 661 8 1.23 6.95
Armenia 9492 210 2.26 139 8 6.11 1.46
Czechia 9302 34 0.37 321 1 0.31 3.45
Norway 8446 6 0.07 236 0 0.00 2.79
Moldova 8360 109 1.32 305 10 3.39 3.65
Ghana 8070 0 0.00 36 0 0.00 0.45
Malaysia 7857 38 0.49 115 0 0.00 1.46
Morocco 7833 26 0.33 205 0 0.00 2.62
Australia 7221 19 0.26 102 -1 -0.97 1.41
Finland 6885 26 0.38 318 -2 -0.62 4.62
Iraq 6868 429 6.66 215 10 4.88 3.13
Cameroon 6397 493 8.35 199 8 4.19 3.11
Azerbaijan 5662 168 3.06 68 5 7.94 1.20
Honduras 5362 160 3.08 217 5 2.36 4.05
Guatemala 5336 249 4.89 116 8 7.41 2.17
Sudan 5173 147 2.92 298 12 4.20 5.76
Luxembourg 4019 1 0.02 110 0 0.00 2.74
Tajikistan 4013 83 2.11 47 0 0.00 1.17
Hungary 3892 16 0.41 527 1 0.19 13.54
Guinea 3844 138 3.72 23 0 0.00 0.60
Senegal 3739 94 2.58 42 0 0.00 1.12
Uzbekistan 3702 79 2.18 15 0 0.00 0.41
Djibouti 3569 215 6.41 24 0 0.00 0.67
Congo (Kinshasa) 3195 125 4.07 72 0 0.00 2.25
Thailand 3082 1 0.03 57 0 0.00 1.85
Cote d’Ivoire 2951 118 4.17 33 0 0.00 1.12
Greece 2918 1 0.03 179 4 2.29 6.13
Gabon 2655 0 0.00 17 0 0.00 0.64
El Salvador 2582 65 2.58 46 0 0.00 1.78
Bosnia and Herzegovina 2524 14 0.56 154 1 0.65 6.10
Bulgaria 2519 6 0.24 140 0 0.00 5.56
North Macedonia 2315 89 4.00 140 7 5.26 6.05
Croatia 2246 0 0.00 103 0 0.00 4.59
Haiti 2226 102 4.80 45 1 2.27 2.02
Cuba 2083 38 1.86 83 0 0.00 3.98
Somalia 2023 47 2.38 79 1 1.28 3.91
Kenya 2021 59 3.01 69 5 7.81 3.41
Estonia 1870 1 0.05 68 0 0.00 3.64
Maldives 1829 56 3.16 6 1 20.00 0.33
Kyrgyzstan 1817 69 3.95 16 0 0.00 0.88
Nepal 1811 239 15.20 8 0 0.00 0.44
Iceland 1806 0 0.00 10 0 0.00 0.55
Lithuania 1678 3 0.18 70 0 0.00 4.17
Venezuela 1662 152 10.07 17 3 21.43 1.02
Sri Lanka 1643 10 0.61 11 1 10.00 0.67
Slovakia 1522 1 0.07 28 0 0.00 1.84
New Zealand 1504 0 0.00 22 0 0.00 1.46
Slovenia 1473 0 0.00 109 1 0.93 7.40
Guinea-Bissau 1339 83 6.61 8 0 0.00 0.60
Mali 1315 50 3.95 78 1 1.30 5.93
Equatorial Guinea 1306 0 0.00 12 0 0.00 0.92
Ethiopia 1257 85 7.25 12 1 9.09 0.95
Lebanon 1233 13 1.07 27 0 0.00 2.19
Albania 1143 6 0.53 33 0 0.00 2.89
Zambia 1089 32 3.03 7 0 0.00 0.64
Costa Rica 1084 28 2.65 10 0 0.00 0.92
Tunisia 1084 7 0.65 48 0 0.00 4.43
Central African Republic 1069 58 5.74 4 2 100.00 0.37
Latvia 1066 0 0.00 24 0 0.00 2.25
Kosovo 1064 0 0.00 30 0 0.00 2.82

In Depth USA Stats (State Wise Figures)

Confirmed Cases and Deaths- States of USA (With Fatality Rates)

State Confirmed NewConfirmations CasesPercentIncrease Deaths NewDeaths DeathsPercentIncrease FatalityRate ConfirmedCasesPerMillPopl DeathsPerMillPopl InfectionOdds
New York 371711 941 0.25 29917 133 0.45 8.05 19107.61 1537.87 1 in 52
New Jersey 160918 473 0.29 11723 25 0.21 7.29 18116.93 1319.83 1 in 55
Illinois 121234 974 0.81 5412 22 0.41 4.46 9567.21 427.09 1 in 105
California 114733 2782 2.49 4217 45 1.08 3.68 2903.73 106.73 1 in 344
Massachusetts 100805 3840 3.96 7035 189 2.76 6.98 14505.35 1012.30 1 in 69
Pennsylvania 76646 517 0.68 5567 12 0.22 7.26 5987.04 434.85 1 in 167
Texas 65593 941 1.46 1683 8 0.48 2.57 2262.15 58.04 1 in 442
Michigan 57532 135 0.24 5516 25 0.46 9.59 5760.77 552.33 1 in 174
Florida 56830 667 1.19 2460 9 0.37 4.33 2646.00 114.54 1 in 378
Maryland 53327 549 1.04 2552 20 0.79 4.79 8820.68 422.12 1 in 113
Georgia 47902 839 1.78 2094 41 2.00 4.37 4511.64 197.22 1 in 222
Virginia 45398 791 1.77 1392 17 1.24 3.07 5318.72 163.08 1 in 188
Connecticut 42740 539 1.28 3970 26 0.66 9.29 11987.81 1113.51 1 in 83
Louisiana 40341 425 1.06 2801 10 0.36 6.94 8677.73 602.52 1 in 115
Ohio 35984 471 1.33 2207 52 2.41 6.13 3078.42 188.81 1 in 325
Indiana 34830 256 0.74 2143 9 0.42 6.15 5173.63 318.32 1 in 193
North Carolina 29592 807 2.80 948 11 1.17 3.20 2821.49 90.39 1 in 354
Colorado 26563 199 0.75 1458 13 0.90 5.49 4612.64 253.18 1 in 217
Minnesota 25208 358 1.44 1060 10 0.95 4.21 4469.80 187.96 1 in 224
Tennessee 22566 0 0.00 364 0 0.00 1.61 3302.42 53.27 1 in 303
Washington 21977 275 1.27 1123 5 0.45 5.11 2886.05 147.47 1 in 346
Arizona 20129 193 0.97 918 11 1.21 4.56 2643.37 120.55 1 in 378
Iowa 19699 147 0.75 555 20 3.74 2.82 6243.60 175.91 1 in 160
Alabama 18630 678 3.78 646 16 2.54 3.47 3799.57 131.75 1 in 263
Wisconsin 18543 140 0.76 595 3 0.51 3.21 3184.75 102.19 1 in 314
Mississippi 15752 229 1.48 739 5 0.68 4.69 5292.75 248.31 1 in 189
Rhode Island 14991 63 0.42 720 2 0.28 4.80 14150.98 679.65 1 in 71
Nebraska 14345 244 1.73 170 0 0.00 1.19 7415.71 87.88 1 in 135
Missouri 13724 286 2.13 776 0 0.00 5.65 2236.12 126.44 1 in 447
South Carolina 12148 287 2.42 500 6 1.21 4.12 2359.42 97.11 1 in 424
Kentucky 10046 342 3.52 439 8 1.86 4.37 2248.60 98.26 1 in 445
Utah 9999 202 2.06 113 0 0.00 1.13 3118.88 35.25 1 in 321
Kansas 9920 220 2.27 217 2 0.93 2.19 3405.06 74.49 1 in 294
Delaware 9605 107 1.13 368 2 0.55 3.83 9863.79 377.91 1 in 101
District of Columbia 8857 56 0.64 468 2 0.43 5.28 12549.79 663.13 1 in 80
Nevada 8702 74 0.86 417 0 0.00 4.79 2825.18 135.38 1 in 354
New Mexico 7800 111 1.44 362 6 1.69 4.64 3719.90 172.64 1 in 269
Arkansas 7443 190 2.62 133 0 0.00 1.79 2466.35 44.07 1 in 405
Oklahoma 6913 495 7.71 350 16 4.79 5.06 1747.04 88.45 1 in 572
South Dakota 5034 41 0.82 62 0 0.00 1.23 5690.33 70.08 1 in 176
New Hampshire 4685 34 0.73 245 0 0.00 5.23 3445.59 180.19 1 in 290
Oregon 4302 59 1.39 154 1 0.65 3.58 1019.98 36.51 1 in 980
Puerto Rico 3873 97 2.57 136 0 0.00 3.51 1212.70 42.58 1 in 825
Idaho 2839 0 0.00 82 0 0.00 2.89 1584.21 45.76 1 in 631
North Dakota 2625 48 1.86 61 0 0.00 2.32 3444.60 80.05 1 in 290
Maine 2349 24 1.03 89 0 0.00 3.79 1747.49 66.21 1 in 572
West Virginia 2028 18 0.90 76 1 1.33 3.75 1134.77 42.53 1 in 881
Vermont 983 2 0.20 55 0 0.00 5.60 1575.35 88.14 1 in 635
Wyoming 910 7 0.78 17 1 6.25 1.87 1572.33 29.37 1 in 636
Hawaii 652 0 0.00 17 0 0.00 2.61 460.49 12.01 1 in 2172
Montana 519 4 0.78 17 0 0.00 3.28 485.60 15.91 1 in 2059
Alaska 466 7 1.53 10 0 0.00 2.15 637.01 13.67 1 in 1570

US Tested- Confirmed Funnel (All States)

State Level Figures

State Tested Confirmed ConfirmationRate TestsPerMillPopl
New York 2113777 371711 17.59 108657.59
New Jersey 795600 160918 20.23 89572.50
Illinois 918273 121234 13.20 72465.75
California 2012583 114733 5.70 50935.71
Massachusetts 592853 100805 17.00 85308.69
Pennsylvania 462329 76646 16.58 36113.84
Texas 970031 65593 6.76 33454.10
Michigan 568023 57532 10.13 56877.05
Florida 1040400 56830 5.46 48440.86
Maryland 308730 53327 17.27 51066.22
Georgia 471631 47902 10.16 44420.48
Virginia 324719 45398 13.98 38043.26
Connecticut 261390 42740 16.35 73315.28
Louisiana 387370 40341 10.41 83326.99
Ohio 398066 35984 9.04 34054.46
Indiana 265896 34830 13.10 39496.04
North Carolina 421908 29592 7.01 40227.37
Colorado 186376 26563 14.25 32364.05
Minnesota 255592 25208 9.86 45320.69
Tennessee 448493 22566 5.03 65634.65
Washington 360899 21977 6.09 47393.84
Arizona 228070 20129 8.83 29950.52
Iowa 159081 19699 12.38 50420.75
Alabama 223523 18630 8.33 45587.31
Wisconsin 272138 18543 6.81 46739.56
Mississippi 176254 15752 8.94 59222.17
Rhode Island 156835 14991 9.56 148046.79
Nebraska 103665 14345 13.84 53590.04
Missouri 199708 13724 6.87 32539.36
South Carolina 204688 12148 5.93 39755.17
Kentucky 216046 10046 4.65 48357.61
Utah 218112 9999 4.58 68033.33
Kansas 95241 9920 10.42 32691.64
Delaware 62447 9605 15.38 64129.50
District of Columbia 47263 8857 18.74 66968.57
Nevada 146783 8702 5.93 47654.40
New Mexico 199604 7800 3.91 95193.27
Arkansas 133236 7443 5.59 44149.68
Oklahoma 193273 6913 3.58 48843.67
South Dakota 45661 5034 11.02 51614.24
New Hampshire 72456 4685 6.47 53287.79
Oregon 131618 4302 3.27 31205.83
Puerto Rico 3873 3873 100.00 1212.70
Idaho 46697 2839 6.08 26057.65
North Dakota 73301 2625 3.58 96187.71
Maine 49633 2349 4.73 36923.49
West Virginia 98095 2028 2.07 54889.16
Vermont 35326 983 2.78 56613.18
Wyoming 25147 910 3.62 43449.86
Hawaii 48487 652 1.34 34245.33
Montana 40657 519 1.28 38040.64
Alaska 54190 466 0.86 74076.10

In Depth India Stats (State Wise Figures)

Confirmed Cases and Deaths (States of India)

State Confirmed NewConfirmations CasesPercentIncrease Recovered RecoveryRate Active Deaths NewDeaths DeathsPercentIncrease FatalityRate
Maharashtra 70013 2358 3.49 30108 43.00 37543 2362 76 3.32 3.37
Tamil Nadu 23495 1162 5.20 13170 56.05 10138 187 11 6.25 0.80
Delhi 20834 990 4.99 8746 41.98 11565 523 50 10.57 2.51
Gujarat 17217 423 2.52 10780 62.61 5374 1063 25 2.41 6.17
Rajasthan 9100 269 3.05 6213 68.27 2688 199 4 2.05 2.19
Uttar Pradesh 8361 286 3.54 5030 60.16 3109 222 5 2.30 2.66
Madhya Pradesh 8283 194 2.40 5003 60.40 2922 358 8 2.29 4.32
State Unassigned 6414 784 13.93 0 0.00 6414 0 0 NaN 0.00
West Bengal 5772 271 4.93 2306 39.95 3141 325 8 2.52 5.63
Bihar 3945 138 3.62 1741 44.13 2181 23 0 0.00 0.58
Andhra Pradesh 3676 105 2.94 2374 64.58 1238 64 2 3.23 1.74
Karnataka 3408 187 5.81 1328 38.97 2026 52 1 1.96 1.53
Telangana 2792 94 3.48 1491 53.40 1213 88 6 7.32 3.15
Jammu and Kashmir 2601 155 6.34 946 36.37 1624 31 3 10.71 1.19
Haryana 2356 265 12.67 1055 44.78 1280 21 1 5.00 0.89
Punjab 2301 38 1.68 2000 86.92 257 44 -1 -2.22 1.91
Odisha 2104 156 8.01 1245 59.17 850 9 0 0.00 0.43
Assam 1486 146 10.90 285 19.18 1194 4 0 0.00 0.27
Kerala 1327 57 4.49 608 45.82 708 11 1 10.00 0.83
Uttarakhand 959 52 5.73 222 23.15 729 5 0 0.00 0.52
Jharkhand 661 26 4.09 296 44.78 360 5 0 0.00 0.76
Chhattisgarh 548 45 8.95 121 22.08 426 1 0 0.00 0.18
Tripura 423 107 33.86 173 40.90 250 0 0 NaN 0.00
Himachal Pradesh 340 10 3.03 118 34.71 213 6 0 0.00 1.76
Chandigarh 297 4 1.37 214 72.05 79 4 0 0.00 1.35
Manipur 83 12 16.90 11 13.25 72 0 0 NaN 0.00
Puducherry 79 9 12.86 25 31.65 54 0 0 NaN 0.00
Ladakh 77 0 0.00 47 61.04 30 0 0 NaN 0.00
Goa 73 2 2.82 50 68.49 23 0 0 NaN 0.00
Nagaland 43 0 0.00 0 0.00 43 0 0 NaN 0.00
Andaman and Nicobar Islands 33 0 0.00 33 100.00 0 0 0 NaN 0.00
Meghalaya 28 1 3.70 12 42.86 15 1 0 0.00 3.57
Arunachal Pradesh 20 16 400.00 1 5.00 19 0 0 NaN 0.00
Mizoram 13 12 1200.00 1 7.69 12 0 0 NaN 0.00
Dadra and Nagar Haveli and Daman and Diu 3 1 50.00 1 33.33 2 0 0 NaN 0.00
Sikkim 1 0 0.00 0 0.00 1 0 0 NaN 0.00
Lakshadweep 0 0 NaN 0 NaN 0 0 0 NaN NaN

In Depth Italy Stats (Region Wise Figures)

Confirmed Cases and Deaths- Regions of Italy (With Fatality and Confirmation Rates)

Region Swabs Confirmations NewConfirmations CasesPercentIncrease ConfirmationRate HospitalizedWithSymptoms IntensiveCare ActiveCases Deceased FatalityRate
Lombardia 757446 89018 50 0.06 11.75 3085 167 20861 16131 18.12
Piemonte 321476 30658 21 0.07 9.54 904 54 5062 3876 12.64
Emilia-Romagna 329358 27809 19 0.07 8.44 383 54 3068 4124 14.83
Veneto 675934 19154 2 0.01 2.83 110 6 1468 1918 10.01
Toscana 253845 10107 3 0.03 3.98 85 25 1082 1048 10.37
Liguria 107787 9719 56 0.58 9.02 191 7 611 1467 15.09
Lazio 257563 7738 10 0.13 3.00 594 56 2894 739 9.55
Marche 103994 6730 0 0.00 6.47 63 9 1327 987 14.67
Campania 203858 4806 4 0.08 2.36 224 6 939 413 8.59
Puglia 119650 4498 4 0.09 3.76 140 11 1155 506 11.25
P.A. Trento 89235 4432 2 0.05 4.97 14 3 293 462 10.42
Sicilia 151186 3443 0 0.00 2.28 65 8 967 274 7.96
Friuli Venezia Giulia 135431 3274 1 0.03 2.42 40 2 266 335 10.23
Abruzzo 76924 3245 1 0.03 4.22 113 6 744 408 12.57
P.A. Bolzano 67121 2598 1 0.04 3.87 13 4 123 291 11.20
Umbria 70741 1431 0 0.00 2.02 15 2 31 76 5.31
Sardegna 57687 1357 1 0.07 2.35 23 1 161 131 9.65
Valle d’Aosta 15230 1187 3 0.25 7.79 11 0 17 143 12.05
Calabria 70892 1158 0 0.00 1.63 20 1 135 97 8.38
Molise 14819 436 0 0.00 2.94 2 2 135 22 5.05
Basilicata 29956 399 0 0.00 1.33 4 0 28 27 6.77

In Depth Canada Stats (With Province Level Figures)

Confirmed Cases and Deaths- Provinces of Canada (With Fatality Rates)

Province Confirmed NewConfirmations CasesPercentIncrease Deaths NewDeaths DeathsPercentIncrease FatalityRate ConfirmedCasesPerMillPopl DeathsPerMillPopl InfectionOdds
Quebec 51354 295 0.58 4661 20 0.43 9.08 6014.99 545.93 1 in 166
Ontario 29845 455 1.55 2353 9 0.38 7.88 2028.64 159.94 1 in 493
Alberta 7044 34 0.49 143 0 0.00 2.03 1596.14 32.40 1 in 627
British Columbia 2597 24 0.93 165 1 0.61 6.35 508.13 32.28 1 in 1968
Nova Scotia 1057 1 0.09 60 0 0.00 5.68 1081.38 61.38 1 in 925
Saskatchewan 646 0 0.00 11 0 0.00 1.70 546.69 9.31 1 in 1829
Manitoba 295 0 0.00 7 0 0.00 2.37 214.15 5.08 1 in 4670
Newfoundland and Labrador 261 0 0.00 3 0 0.00 1.15 500.61 5.75 1 in 1998
New Brunswick 132 0 0.00 0 0 NaN 0.00 169.23 0.00 1 in 5909
Prince Edward Island 27 0 0.00 0 0 NaN 0.00 170.72 0.00 1 in 5858
Yukon 11 0 0.00 0 0 NaN 0.00 267.78 0.00 1 in 3734
Northwest Territories 5 0 0.00 0 0 NaN 0.00 111.35 0.00 1 in 8981

In Depth China Stats (With Province Level Figures)

Confirmed Cases and Deaths- Provinces of China (With Fatality Rates)

Province Confirmed Deaths FatalityRate
Hubei 68135 4512 6.62
Guangdong 1596 8 0.50
Henan 1276 22 1.72
Zhejiang 1268 1 0.08
Hong Kong 1087 4 0.37
Hunan 1019 4 0.39
Anhui 991 6 0.61
Heilongjiang 945 13 1.38
Jiangxi 937 1 0.11
Shandong 792 7 0.88
Shanghai 673 7 1.04
Jiangsu 653 0 0.00
Beijing 593 9 1.52
Chongqing 579 6 1.04
Sichuan 577 3 0.52
Fujian 358 1 0.28
Hebei 328 6 1.83
Shaanxi 309 3 0.97
Guangxi 254 2 0.79
Inner Mongolia 235 1 0.43
Shanxi 198 0 0.00
Tianjin 192 3 1.56
Yunnan 185 2 1.08
Hainan 169 6 3.55
Jilin 155 2 1.29
Liaoning 149 2 1.34
Guizhou 147 2 1.36
Gansu 139 2 1.44
Xinjiang 76 3 3.95
Ningxia 75 0 0.00
Macau 45 0 0.00
Qinghai 18 0 0.00
Tibet 1 0 0.00

Time Series Curves (Top 20 Countries with the Highest Cases)

The time series curves (both linear and logarithmic) are printed for the top 20 countries with the most confirmed COVID-19 cases as of today in decreasing order of confirmations.

Confirmed Cases Count (Linear)

Country Wise Time Series Curve

Confirmed Cases Count (Logarithmic)

Country Wise Time Series Curve

Time Series Curves (Top 20 Countries with the Highest Deaths)

The time series curves (both linear and logarithmic) are printed for the top 20 countries with the most COVID-19 deaths as of today in decreasing order of confirmations.

Death Count (Linear)

Country Wise Time Series Curve

Death Count (Logarithmic)

Country Wise Time Series Curve

Epidemic Curve: Delta in the past 24 hrs (Top 20 Countries with the Highest Cases)

The COVID-19 epidemic curve, also known as an COVID-19 epi curve or COVID-19 epidemiological curve, is a statistical chart to visualise the onset and progression of the COVID-19 outbreak in various countries. The term flattening of the epidermic curve is referred to as the drastic reduction of new cases which can be seen in the dip in the number of new cases in the past 24 hrs. The below charts show if this has happened for the worst affected 20 countries in the world as of today. The fitted line in the below bars show the last 7 day average of new cases/ new deaths.

Delta in Confirmed Cases

Number of New Cases in the past 24 hrs

Delta in Deaths

Number of Deaths in the past 24 hrs

Measuring Outbreak Velocity: 5 Day Lagging Average Doubling Time (Top 20 Countries with the Highest Cases)

The velocity of an outbreak is determined by a construct known as doubling time. This value describes the number of days, on average, required for the number of cases to double in a given area. For our analysis we use average doubling time, which can be defined as the number of days, on average, required for the average number of COVID-19 cases to double in a given area.

This measure can describe COVID-19 behavior worldwide, in a country, or even in a smaller region such as a state. For our analysis, we will discuss average doubling time at a national level for the top 20 most affected countries.

Below, we have calculated average doubling time for several nations, on a trailing, rolling 5-day basisbased on today’s case values. A decline in average doubling time indicates that the COVID-19 outbreak (confirmation rate) is accelerating (average cases double in fewer days), while an increase of average doubling time indicates that the outbreak is slowing.

Ideally, when social distancing and lockdowns are implemented aggressively in a country and after some period of delay, doubling times should begin to increase in a matter of days, weeks, or months, depending upon the severity of the epidemic and the degree of social distancing achievable.

Given the fact that many countries across the world have already enacted or implemented social distancing measures, this is why one should be cautious not to extrapolate COVID-19 growth rates from trailing statistics.

5 Day Lagging Avg Doubling Time of Confirmations

Confirmed Cases and Deaths Per Million Population and Infection Odds

This metric confirmed cases per million population and deaths per million population shows the extent to which the disease has spread with respect to the population of the country. The metric Infection Odds shows 1 in how many people are infected with COVID-19 in the corresponding country.

For the top 20 countries with most confirmed cases excluding cruise ships

Country_Region ConfirmedCasesPerMillionPopl DeathsPerMillionPopl InfectionOdds
US 5535.94 321.41 1 in 181
Brazil 2515.27 143.03 1 in 398
Russia 2867.32 33.56 1 in 349
United Kingdom 4180.25 588.91 1 in 239
Spain 5135.83 581.38 1 in 195
Italy 3855.77 553.49 1 in 259
India 148.15 4.19 1 in 6750
France 2826.51 430.45 1 in 354
Germany 2217.59 103.33 1 in 451
Peru 5285.64 144.05 1 in 189
Turkey 2038.97 56.47 1 in 490
Iran 1902.97 97.07 1 in 525
Chile 5825.93 61.66 1 in 172
Mexico 723.18 78.69 1 in 1383
Canada 2481.72 196.97 1 in 403
Saudi Arabia 2645.48 15.94 1 in 378
China 60.72 3.35 1 in 16470
Pakistan 367.82 7.83 1 in 2719
Belgium 5133.07 832.11 1 in 195
Qatar 22142.10 15.16 1 in 45

US Detailed State and County Level Curves

This section of the report might be of interest to people who want an an accurate data oriented picture of the 2019- 2020 COVID-19 pandemic at the state/ county level in USA.

Epidemic Curve: Delta in Confirmed Cases in US States

The COVID-19 epidemic curve, also known as an COVID-19 epi curve or COVID-19 epidemiological curve, is a statistical chart to visualise the onset and progression of the COVID-19 outbreak in various US states. The term flattening of the epidermic curve is referred to as the drastic reduction of new cases which can be seen in the dip in the number of new cases in the past 24 hrs. The below charts show if this has happened for the worst affected 20 states in USA as of today. The fitted line in the below bars show the last 7 day average of new cases/ new deaths.

Number of New Cases in the past 24 hrs

Epidermic Curve: Delta in Deaths in US States

Number of Deaths in the past 24 hrs

Top 50 US Counties with the Highest Cases and Deaths

All NYC boroughs are mentioned together as New York County

County State Confirmations Deaths FatalityRate
New York New York 203764 21607 10.60
Cook Illinois 78495 3658 4.66
Los Angeles California 56011 2386 4.26
Nassau New York 40479 2125 5.25
Suffolk New York 39705 1906 4.80
Westchester New York 33552 1374 4.10
Philadelphia Pennsylvania 22881 1320 5.77
Middlesex Massachusetts 22224 1650 7.42
Wayne Michigan 20446 2463 12.05
Hudson New Jersey 18801 1183 6.29
Suffolk Massachusetts 18581 896 4.82
Bergen New Jersey 18302 1580 8.63
Miami-Dade Florida 18139 702 3.87
Essex New Jersey 17733 1667 9.40
Passaic New Jersey 16200 929 5.73
Middlesex New Jersey 15977 996 6.23
Union New Jersey 15858 1074 6.77
Fairfield Connecticut 15709 1288 8.20
Prince George’s Maryland 15353 545 3.55
Essex Massachusetts 14721 968 6.58
Rockland New York 13185 646 4.90
Harris Texas 12664 235 1.86
New Haven Connecticut 11479 974 8.49
Montgomery Maryland 11476 616 5.37
Worcester Massachusetts 11352 779 6.86
Fairfax Virginia 11219 387 3.45
Providence Rhode Island 11052 0 0.00
Dallas Texas 10462 229 2.19
Hartford Connecticut 10448 1259 12.05
Orange New York 10422 444 4.26
Maricopa Arizona 9937 433 4.36
Marion Indiana 9900 581 5.87
District of Columbia District of Columbia 8857 468 5.28
Ocean New Jersey 8770 740 8.44
Norfolk Massachusetts 8586 841 9.80
Hennepin Minnesota 8514 616 7.24
Lake Illinois 8408 292 3.47
Oakland Michigan 8407 992 11.80
Monmouth New Jersey 8249 599 7.26
Plymouth Massachusetts 8200 562 6.85
King Washington 8123 569 7.00
Riverside California 7982 331 4.15
Milwaukee Wisconsin 7799 299 3.83
DuPage Illinois 7765 374 4.82
Jefferson Louisiana 7652 451 5.89
San Diego California 7481 269 3.60
Bristol Massachusetts 7348 429 5.84
Broward Florida 7196 314 4.36
Orleans Louisiana 7141 507 7.10
Montgomery Pennsylvania 7093 686 9.67

Overall US Choropleth Map

Choropleths are an ideal way to visualize the past/ current COVID-19 hotspots within a country. The below are the hotspots in the US.

County level COVID-19 Confirmations Map

Canada Detailed Province Level Curves

This section of the report might be of interest to people who want an an accurate data oriented picture of the 2019- 2020 COVID-19 pandemic at the province level in Canada.

The COVID-19 epidemic curve, also known as an COVID-19 epi curve or COVID-19 epidemiological curve, is a statistical chart to visualise the onset and progression of the COVID-19 outbreak in the most affected Canadian provinces- Quebec, Ontario, Alberta and British Columbia. The term flattening of the epidermic curve is referred to as the drastic reduction of new cases which can be seen in the dip in the number of new cases in the past 24 hrs. The fitted line in the below bars show the last 7 day average of new cases/ new deaths.

Epidemic Curve: Delta in Confirmed Cases in Canadian Provinces

Number of New Cases in the past 24 hrs

Epidermic Curve: Delta in Deaths in Canadian Provinces

Number of Deaths in the past 24 hrs

Data Sources

CSSEGISandData, The NY Times, amodm/api-covid19-in and pcm-dpc